Background Extremely important diagnostic tool eliminates need for exploratory surgery XRay Computed Tomography CT 3 Steps Injection of radioopaque dye iodine Acquisition and 3D reconstruction of 2D images ID: 631450
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Slide1
Aortic Lumen Detection
Brad Wendorff, ECE 539Slide2
Background
Extremely important diagnostic tool – eliminates need for “exploratory surgery”
X-Ray Computed Tomography (CT)
3 Steps
Injection of radio-opaque dye (iodine)
Acquisition and 3D reconstruction of 2D images
Creation of angiograms via 3D reconstruction or
reprojection
of 2D sectionsSlide3
Motivation
Physicians are often interested in specific regions
Pre-processing may be required to remove impeding or irrelevant structures
Current pre-processing methods require manual tracing of regions of interest
TIME INTENSIVE – CT scans contain hundreds of 2D images
Manual pre-processing is difficult to reproduceIncrease accuracy and efficiency by automatingSlide4
Design Considerations
Attenuation within blood vessels may vary thus affecting Hounsfield Unit values
Measured attenuation may be corrupted by CT artifacts
Calcium
Thrombus
Iodine enhances only vascular lumen – It does not perfuse into areas of thrombus uniformlySemiautomatedSlide5
3D Reconstruction
Aortic LumenSlide6
Method of DetectionSlide7
K-means Clustering
Assign data points (voxels) to the cluster with the closest center
Continues to aggregate data points into each cluster until no changes occur
Implement this strategy on a series of axial slices
Extract cluster representing the aortic lumenSlide8
Analysis of Results
Quality of results is based on a comparison with segmentation produced by Industry Standard program
TeraRecon
iNtuition
Cluster diameters will be compared to manually edited segmentation in TeraReconSlide9
Questions?Slide10
References
S.
Shiffman
, G. D. Rubin, and S.
Napel
, Semiautomated editing of computed tomography sections for visualization of vasculature, vol. 2707, SPIE, 1996. http://www.siue.edu/~sumbaug/RetinalProjectPapers/Review%20of%20Blood%20Vessel%20Extraction%20Techniques%20and%20Algorithms.pdf